scholarly journals Analysis of the impact of construction of selected water reservoirs on the surrounding environment made on the basis of satellite data

2018 ◽  
Vol 63 ◽  
pp. 00008
Author(s):  
Boguslawa Kwoczynska ◽  
Izabela Piech ◽  
Rafal Wozniak
Keyword(s):  
Land Use ◽  
Satellite Imagery ◽  
Satellite Data ◽  
Water Reservoirs ◽  
Land Use Structure ◽  
Surrounding Environment ◽  
Before And After ◽  
Reservoir Construction ◽  
The Impact ◽  
Test Objects

The authors aimed at showing in the publication the impact of the construction of selected water reservoirs in Poland on the surrounding environment, basing on the satellite imagery. For this purpose, for four test objects, i.e. the Dobczyce Reservoir, the Klimkow Reservoir, the Czorsztyn Reservoir and the Domaniowski Reservoir analyzes were carried out concerning the changes in the structure of land use for the state before and after reservoir construction, and indicators such as NDWI, SAVI and TSAVI were calculated. In the case of the analysis of changes in the land use structure, the direction of these changes was determined first of all, and for SAVI and TSAVI indices, the percentage change in their value and the direction of these changes were calculated.

scholarly journals Evaluating Satellite Imagery‐Based Land Use Data for Describing Forestland Development in Western Washington

2009 ◽  
Vol 24 (4) ◽  
pp. 214-222 ◽  
Author(s):  
Jeffrey D. Kline ◽  
Alissa Moses ◽  
David Azuma ◽  
Andrew Gray
Keyword(s):  
Land Use ◽  
Satellite Imagery ◽  
Econometric Model ◽  
Landsat Imagery ◽  
Forest Inventory And Analysis ◽  
The Us ◽  
Western Washington ◽  
Us Census ◽  
The Impact ◽  
Density Development

Abstract Forestry professionals are concerned about how forestlands are affected by residential and other development. To address those concerns, researchers must find appropriate data with which to describe and evaluate rates and patterns of forestland development and the impact of development on the management of remaining forestlands. We examine land use data gathered from Landsat imagery for western Washington and evaluate its usefulness for characterizing low-density development of forestland. We evaluate the accuracy of the satellite imagery‐based land use classifications by comparing them with other data from US Forest Service's Forest Inventory and Analysis inventories and the US census. We then use the data to estimate an econometric model describing development as a function of socioeconomic and topographic factors and project future rates of development and forestland loss to 2020. We conclude by discussing how best to meet the land use data needs of researchers, forestry policymakers, and managers.

scholarly journals Assessing the Impact of Floods Disaster on Soil Erosion Risk Based on the RUSLE-GloSEM Approach in Western Iran

2021 ◽  
Author(s):  
Morteza Akbari ◽  
Ehsan Neamatollahi ◽  
Hadi Memarian ◽  
Mohammad Alizadeh Noughani
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Soil Erosion ◽  
Land Use Change ◽  
Agricultural Development ◽  
Erosion Risk ◽  
Before And After ◽  
Global Soil ◽  
Major Floods ◽  
The Impact

Abstract Floods cause great damage to ecosystems and are among the main agents of soil erosion. Given the importance of soils for the functioning of ecosystems and development and improvement of bio-economic conditions, the risk and rate of soil erosion was assessed using the RUSLE model in Iran’s Lorestan province before and after a period of major floods in late 2018 and early 2019. Furthermore, soil erosion was calculated for current and future conditions based on the Global Soil Erosion Modeling Database (GloSEM). The results showed that agricultural development and land use change are the main causes of land degradation in the southern and central parts of the study area. The impact of floods was also significant since our evaluations showed that soil erosion increased from 4.12 t ha-1 yr-1 before the floods to 10.93 t ha-1 yr-1 afterwards. Field surveying using 64 ground control points determined that erodibility varies from 0.17 to 0.49% in the study area. Orchards, farms, rangelands and forests with moderate or low vegetation cover were the most vulnerable land uses to soil erosion. The GloSEM modeling results revealed that climate change is the main cause of change in the rate of soil erosion. Combined land use change-climate change simulation showed that soil erosion will increase considerably in the future under SSP1-RCP2.6, SSP2-RCP4.5, and SSP5-RCP8.5 scenarios. In the study area, both natural factors, i.e. climate change and human factors such as agricultural development, population growth, and overgrazing are the main drivers of soil erosion.

Analyze the Impact of the Thin-Walled Hollow Pier by Construction of Reservoir

2013 ◽  
Vol 438-439 ◽  
pp. 1262-1264
Author(s):  
Ke Dong Tang ◽  
Feng Gui Jin
Keyword(s):  
Finite Element ◽  
Realistic Model ◽  
Finite Element Software ◽  
Before And After ◽  
Reservoir Construction ◽  
Thin Walled ◽  
The Impact

The river dam intends to build at 280m downstream of a built bridge. This paper, using ANSYS finite element software, establishes a rational and realistic model to analyze the influence of the reservoir construction on the thin-walled hollow pier of built bridge. The variation of the stress of the bridge thin-walled hollow pier before and after impounding of the reservoir is given out, which can be as a guidance for future reinforcing the thin-walled hollow pier.

scholarly journals Impact of the Kunming–Bangkok Highway on Land Use Changes along the Route between Laos and Thailand

Land ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 991
Author(s):  
Fangyu Zheng ◽  
Jiuming Huang ◽  
Zhiming Feng ◽  
Chiwei Xiao
Keyword(s):  
Land Use ◽  
Land Use Changes ◽  
Sustainable Use ◽  
Road Construction ◽  
Buffer Zone ◽  
Scientific Basis ◽  
The Road ◽  
Cross Border ◽  
Before And After ◽  
The Impact

Road construction fragments the landscape, reduces connectivity, and drives land use changes. To our knowledge, little is known about the scope and intensity of the effects of cross-border roads on changes in land use. Here, with the land use data products provided by the US Agency for International Development’s SERVIR Mekong project, using the GIS-based spatial analysis to quantitatively analyze and compare the effects of the cross-border road on land use changes within a 30 km buffer area along the Kunming–Bangkok Highway between Laos and Thailand. The results show the following: The greater the distance was from the highway, the smaller were the overall changes in land use within the buffer zone. A comparison of the situation before and after the road was opened in 2013 revealed significant differences in the most influential land use types of agricultural expansion, i.e., from 47.07% to 52.07% (the buffer zone was 1 km). In particular, 57.32% (1381.93 ha) and 40.08% (966.46 ha) of the land occupied by forests had been converted into land for plantation and agriculture, respectively, from 2013 to 2018. The scope of the impact of the operational route on the dynamics of land use was inconsistent. The largest impact before the road became operational was within 4 km of the buffer zone (0.26 to 0.24). Once the road had been opened, the range of its impact was beyond 10 km (0.63 to 0.57). The work here can provide a scientific basis for regional transportation planning and the sustainable use of land resources.

scholarly journals Variability in development of the land use intensity in agricultural companies

2011 ◽  
Vol 59 (4) ◽  
pp. 349-354
Author(s):  
Eliška Svobodová ◽  
Karel Vinohradský
Keyword(s):  
Land Use ◽  
Agricultural Land ◽  
Agricultural Area ◽  
Special Focus ◽  
Land Use Intensity ◽  
Natural Conditions ◽  
Agricultural Enterprises ◽  
Before And After ◽  
Developmental Differentiation ◽  
The Impact

The aim of this article is to analyse the variability of the intensity of the land use in agricultural enterprises farming in different natural conditions in the years 2001–2006. The main reason for this analysis is the diminishing intensity of agricultural production in the Czech Republic in the nineties as well as in the past decade. This article is a part of the research with special focus on the sings of the extensive and intensive systems of agriculture in the developmental differentiation of agricultural enterprises.As the data source for the analysis made in this article has been used the group of companies NUTS II Southeast in the period 2001–2006, i.e. in the time before and after our joining the EU. The group of companies includes legal entities with agricultural area under cultivation over 1 000 ha and average agricultural area 1 680 ha.The results show that the decrease in the agriculture intensity in the years 2001–2006 reached 179 Czech crowns per hectare and the average Earnings from Produce per hectare is 26 792 Czech crowns per hectare.Beside the variability of the intensity of the agricultural land use, there was also focused how the different natural conditions influence the land use intensity in the enterprises.The results in this article show that there is significant and deepening inter-enterprise differentiation of the level of intensity of farming, but it is also necessary to say, that the impact of various agro-ecological conditions on the development of intensity of farming is not dominant.

The impact of land use change, climate change and reservoir construction on ecosystem services in a Mediterranean catchment

2020 ◽  
Author(s):  
Joris Eekhout ◽  
Carolina Boix-Fayos ◽  
Pedro Pérez-Cutillas ◽  
Joris de Vente
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Ecosystem Services ◽  
Land Use Change ◽  
Urban Expansion ◽  
Land Use Changes ◽  
Sediment Concentration ◽  
Low Flow ◽  
Reservoir Construction ◽  
The Impact

<p>The Mediterranean region has been identified as one of the most affected global hot-spots for climate change. Recent climate change in the Mediterranean can be characterized by faster increasing temperatures than the global mean and significant decreases in annual precipitation. Besides, important land cover changes have occurred, such as reforestation, agricultural intensification, urban expansion and the construction of many reservoirs, mainly with the purpose to store water for irrigation. Here we study the impacts of these changes on several ecosystem services in the Segura River catchment, a typical large Mediterranean catchment where many of the before mentioned changes have occurred in the last half century. We applied a hydrological model, coupled with a soil erosion and sediment transport model, to study the impact of climate and land cover change and reservoir construction on ecosystem services for the period 1971-2010. Eight ecosystem services indicators were defined, which include runoff, plant water stress, hillslope erosion, reservoir sediment yield, sediment concentration, reservoir storage, flood discharge and low flow. To assess larger land use changes, we also applied the model for an extended period (1952-2018) to the Taibilla subcatchment, a typical Mediterranean mountainous subcatchment, which plays an important role in the provision of water within the Segura River catchment. As main results we observed that climate change in the evaluated period is characterized by a decrease in precipitation and an increase in temperature. Detected land use change over the past 50 years is typical for many Mediterranean catchments. Natural vegetation in the headwaters increased due to agricultural land abandonment. Agriculture expanded in the central part of the catchment, which most likely is related to the construction of reservoirs in the same area. The downstream part of the catchment is characterized by urban expansion. While land use changed in more than 30% of the catchment, most impact on ecosystem services can be attributed to climate change and reservoir construction. All these changes have had positive and negative impacts on ecosystem services. The positive impacts include a decrease in hillslope erosion, sediment yield, sediment concentration and flood discharge (-21%, -18%, -82% and -41%, respectively). The negative impacts include an increase in plant water stress (+5%) and a decrease in reservoir storage (-5%). The decrease in low flow caused by land use change was counteracted by an increase in low flow due to reservoir construction. The results of our study highlight how relatively small climate and land use changes compared to the changes foreseen for the coming decades, have had an important impact on ecosystem services over the past 50 years.</p>

scholarly journals Assessment of Deep Learning Techniques for Land Use Land Cover Classification in Southern New Caledonia

2021 ◽  
Vol 13 (12) ◽  
pp. 2257
Author(s):  
Guillaume Rousset ◽  
Marc Despinoy ◽  
Konrad Schindler ◽  
Morgan Mangeas
Keyword(s):  
Land Use ◽  
Deep Learning ◽  
Land Cover ◽  
Satellite Data ◽  
Data Augmentation ◽  
New Caledonia ◽  
Data Set ◽  
Detection Techniques ◽  
Learning Techniques ◽  
The Impact

Land use (LU) and land cover (LC) are two complementary pieces of cartographic information used for urban planning and environmental monitoring. In the context of New Caledonia, a biodiversity hotspot, the availability of up-to-date LULC maps is essential to monitor the impact of extreme events such as cyclones and human activities on the environment. With the democratization of satellite data and the development of high-performance deep learning techniques, it is possible to create these data automatically. This work aims at determining the best current deep learning configuration (pixel-wise vs semantic labelling architectures, data augmentation, image prepossessing, …), to perform LULC mapping in a complex, subtropical environment. For this purpose, a specific data set based on SPOT6 satellite data was created and made available for the scientific community as an LULC benchmark in a tropical, complex environment using five representative areas of New Caledonia labelled by a human operator: four used as training sets, and the fifth as a test set. Several architectures were trained and the resulting classification was compared with a state-of-the-art machine learning technique: XGboost. We also assessed the relevance of popular neo-channels derived from the raw observations in the context of deep learning. The deep learning approach showed comparable results to XGboost for LC detection and over-performed it on the LU detection task (61.45% vs. 51.56% of overall accuracy). Finally, adding LC classification output of the dedicated deep learning architecture to the raw channels input significantly improved the overall accuracy of the deep learning LU classification task (63.61% of overall accuracy). All the data used in this study are available on line for the remote sensing community and for assessing other LULC detection techniques.

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